sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
6bd60ebb86d987777d6134274d3319b47c2fb361a058c27ff9ed5874f974184d | Python | 1,993 | 61 | import numpy as np
import scipy.special as special
from .basic_distributions import Distribution
from ..utils import *
class Binomial(Distribution):
"""
Class to define Binomial distributions
Equations:
p(x|N,theta) = binom(N,x) * theta**(x) * (1-theta)**(N-x)
log p(x|N,theta) = log(binom(N,x)) +... |
3a4e7ab8041e5adf50e4f572b6986fb42452074a687210e1f61e77f8b996c235 | Python | 1,994 | 57 | import os
from typing import AsyncIterator, List, Tuple
import ray
from ray.dashboard.modules.job.common import JOB_LOGS_PATH_TEMPLATE
from ray.dashboard.modules.job.utils import fast_tail_last_n_lines, file_tail_iterator
class JobLogStorageClient:
"""
Disk storage for stdout / stderr of driver script logs.
... |
c0362e38fd410ed54a386f4611ee8548c884fd842ffba4f47841ee61273c3642 | Python | 1,994 | 66 | import numpy as np
import torch
from tqdm import trange
def KS(u):
pad_op = torch.nn.CircularPad2d(2)
u = pad_op(u)
ux = (u[:, 3:-1, 2:-2] - u[:, 1:-3, 2:-2]) / 2
uy = (u[:, 2:-2, 3:-1] - u[:, 2:-2, 1:-3]) / 2
ux2 = (ux ** 2 + uy ** 2)
uxx = u[:, 3:-1, 2:-2] + u[:, 1:-3, 2:-2] + u[:... |
2516286ff3dd12a738ee5ad2afdca1865ed83178fda5c1b7877655ef531f7428 | Python | 1,995 | 67 | import numpy as np
import torch
from .base import Transform, randint
class Compose(Transform):
"""Apply transforms in sequence.
Args:
transforms: list of transforms, or a single transform.
"""
def __init__(self, transforms, p=1.0):
super().__init__(p)
if isinstance(transform... |
7b57cfc4a7e7a6d9b63fc8fa5305b561b805afa31752a62a096e7c03dbbd7ca5 | Python | 1,995 | 60 | # Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under th... |
14e8f16d17ba34e442eacfaef80c5402912352d84ef94df8d52a361a8f87c45d | Python | 1,996 | 51 | # coding=utf-8
# Copyright 2023 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... |
18cd35d887d2a4edf977aad9a379d78466d34aebaade2235c9f28310c59fd843 | Python | 1,996 | 29 | SPLICEBERT_PATH = "/path/to/SpliceBERT/models/model_folder" # set the path to the folder of pre-trained SpliceBERT
import torch
from transformers import AutoTokenizer, AutoModel, AutoModelForMaskedLM, AutoModelForTokenClassification
# load tokenizer
tokenizer = AutoTokenizer.from_pretrained(SPLICEBERT_PATH)
# prepar... |
5b9ec0a6e7b531cf9a7a4fbf0b70bed1d5fe12a439c68b3a36bab664dd8303b8 | Python | 1,997 | 66 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
from fairchem.core.components.runner import (
PreemptableMixin,
StopfairDetected,
)
from ._sin... |
40327d563fb05a0eed8483bc921eee152fb8a9e9b91c59b08e59056275335a1f | Python | 1,999 | 55 | from .ssim import SSIM
import torch
class S3IM(torch.nn.Module):
r"""Implements Stochastic Structural SIMilarity(S3IM) algorithm.
It is proposed in the ICCV2023 paper
`S3IM: Stochastic Structural SIMilarity and Its Unreasonable Effectiveness for Neural Fields`.
Arguments:
kernel_size (int)... |
b5ba85b4ab75e304041f5d0cd334a9a63492579d6c44492e164a8fa3cebd7d61 | Python | 1,999 | 35 | from spinnaker2.neuron_models.spike_list import SpikeListApplication
from spinnaker2.neuron_models.float_list import FloatListApplication
from spinnaker2.neuron_models.spike_receiver import SpikeReceiverApplication
from spinnaker2.neuron_models.lif_curr_exp import LIFCurrExpApplication, LIFCurrExpNoDelayApplication
fro... |
ddf994b3f926eda1ed1f559f3c19bc4922905d929c89e9fca53b766347ee671e | Python | 2,000 | 66 | """Apply copyright headers to all code files in the repository.
This file can be called as a python script without arguments. For
configuration, see the instructions in NOTICE.yml.
"""
import fnmatch
import glob
import subprocess
import tempfile
import yaml
def load_config(filename):
with open(filename, "r") a... |
ebff389f472c36fdf637927ca11ad637af7b3c440e654dcd4db1b855f1e4e0ef | Python | 2,001 | 56 | import numpy as np
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import PolynomialFeatures, MinMaxScaler
def train_model(training_set_path):
"""
Train a RandomForestClassifier using the provided training set and return t... |
2476d6ac8af83a888150ed895133f2e907c343d691e81c03ca2d668042a813db | Python | 2,002 | 56 | from mfm import MFM #This is the mean-field model of DBS-LFP. See mfm for details
import numpy as np
import matplotlib.pyplot as plt #Helpful for plotting
import pdb
import pickle as pl
with open('freqVals.p','rb') as f:
freq = pl.load(f)
#Keywards to set up models
kwargsDBSSub = { ... |
40ee52aa7631d4126d05bc6583fba640251c07b7e9d07a22aa83b99f6428a829 | Python | 2,004 | 54 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
b088af3bcb19e924c6821e2ccbb2807f05f01709270d1adce62b87adad61c6a0 | Python | 2,005 | 54 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
import random
import ase
from fairchem.applications.cattsunami.core import Reaction
from fairchem.appl... |
2f7e6a8dea2f17032946698c1114adacc9912c6684dbcb41811013d2e3a86cba | Python | 2,006 | 52 | from argschema import ArgSchema
from argschema.schemas import DefaultSchema
from argschema.fields import (
Nested, String, Int, Float, OutputDir, OutputFile, NumpyArray)
class PiaWmStreamlineSchema(ArgSchema):
"""Arg Schema for run_pia_wm_streamlines"""
pia_path_str = String(
required=True,
... |
e9ec726175f6d425d47a56ca08d68125178f6f8ea22ed122684806b60254239f | Python | 2,007 | 88 | # __return_ray_put_start__
import ray
# Non-fault tolerant version:
@ray.remote
def a():
x_ref = ray.put(1)
return x_ref
x_ref = ray.get(a.remote())
# Object x outlives its owner task A.
try:
# If owner of x (i.e. the worker process running task A) dies,
# the application can no longer get value of ... |
994fc3e8a564953e0c30b551b73c68043ea0a310b02e0eb0b8e108cd74531bb1 | Python | 2,008 | 77 | import numpy as np
from scipy.stats import sem
class SimplePETracker():
def __init__(self, size=512):
self.tracker = {}
self.size = size
def record(self, input, pe, verbose=False):
input_key = str(input)
if not self.input_in_tracker(input_key):
self.tracker[input_... |
0e5a26a48100884665faa4becb87acbc1c90105109332ab6b298965e2b827061 | Python | 2,010 | 66 | import os
import sys
import subprocess as sp
import unittest
import shutil
import tempfile
import xarray as xr
import numpy as np
try:
import dolfinx
has_dolfinx = True
except ImportError:
has_dolfinx = False
@unittest.skipIf(
not has_dolfinx,
"streamline calculation requires conda-installed fen... |
e9960a73f47a9897e7f5915721bf71eab84729dc01b362272a889cc3c66f49ea | Python | 2,010 | 55 | '''
Contains patches for MOABB v0.4.6 to speed up the computation.
Especially useful when multiple permutations of one run are calculated.
Just import the appropriate module to use the patch
moabbpatch.datasets:
Stores the loaded dataset in memory, so that it must not be loaded everytime it is used.
moabbpatch.ba... |
c040026fe20caec35c8e836f1a3a1a41220d1d8b3aea3d1739e4129a4ee78533 | Python | 2,011 | 56 | from copy import deepcopy
from typing import Callable
from warnings import warn
import torch.nn as nn
def replace_module(model: nn.Module, source_class: type, mapper_fn: Callable):
"""A utility function that returns a copy of the model, where specific layers are replaced with
another type depending on the ma... |
51950a828c0193e1998560cb2f8ce93a89b0b3e151dbcd9e0802f06150d76fdf | Python | 2,013 | 54 | import torch
from ..reducers import AvgNonZeroReducer
from ..utils import loss_and_miner_utils as lmu
from ..losses.generic_pair_loss import GenericPairLoss
class ContrastiveLoss(GenericPairLoss):
def __init__(self, pos_margin=0, neg_margin=1, **kwargs):
super().__init__(mat_based_loss=False, **kwargs)
... |
5430a7fd1ec6780881eb8ae4bfd1ce20a2cb33c52782c29cd051919406c0c698 | Python | 2,013 | 64 | # __anti_pattern_start__
import ray
import pickle
from ray._private.internal_api import memory_summary
import ray.exceptions
ray.init()
@ray.remote
def out_of_band_serialization_pickle():
obj_ref = ray.put(1)
import pickle
# object_ref is serialized from user code using a regular pickle.
# Ray can't... |
7ae79c92dd7c2db79921d8c98d52129456c71e23b1465a9d093f9921d602e4ed | Python | 2,013 | 47 | from transformers.modeling_outputs import SequenceClassifierOutput
from torch import nn
class ModelWithCustomLossFunction(nn.Module):
def __init__(self, pretrained_model, pretrained_model_label=None, num_labels=None, dropout=0.3, linear_layer_dim=768, output_attentions=False, output_hidden_states=True):
s... |
06d0b884f7815476091c5d9edad1581f0faf7b5cde1c7e617679833552f33574 | Python | 2,014 | 57 | import os
import argparse
import numpy as np
from sklearn.model_selection import StratifiedShuffleSplit
"""Generate a random split train-val for gridsearch"""
def load_train_data(path, dtype_data=np.uint8, dtype_label=np.uint8):
X = np.fromfile(path + "/X_train.bin", dtype=dtype_data)
y = np.fromfile(path + ... |
36ff9a1849207448939597620184fbc0548f15425f23d8c527921c1af5ebf413 | Python | 2,014 | 44 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
9b6cc2c0f33cf8321c7e615a252ead462bbaadfbeb3e83d1b106d7f0473cb0a1 | Python | 2,014 | 67 |
import logging
import time
from abc import ABCMeta, abstractmethod
from pfrl.experiments import EvaluationHook
from pfrl.experiments import StepHook
class ProgressStepHook(StepHook):
"""
Hook function that will be called in training to log current progress
"""
def __init__(self, log_interval=256, lo... |
f6c90beec6ea41d5d446997c856ea9221831db7bea887b7adc26a973f33eff82 | Python | 2,014 | 83 | import sys
import pytest
from ray._common.logging_constants import (
LOGGER_FLATTEN_KEYS,
LOGRECORD_STANDARD_ATTRS,
LogKey,
)
def test_logrecord_standard_attrs_is_frozenset():
assert isinstance(LOGRECORD_STANDARD_ATTRS, frozenset)
def test_logrecord_standard_attrs_contains_standard_names():
ex... |
c0e6f9221ef8b0965f433c2d1f7e3c14e6af884ab02c4891a5e22ba4921daaf6 | Python | 2,015 | 62 | """ Basic callback definition. """
from sklearn.base import BaseEstimator
__all__ = ['Callback']
class Callback:
"""Base class for callbacks.
All custom callbacks should inherit from this class. The subclass
may override any of the ``on_...`` methods. It is, however, not
necessary to override all ... |
e9ad25065537e4dbc8dc66c3af68e0bb0e14f92a9058a32e0dddc55ed6b187eb | Python | 2,015 | 63 | # --------------------------------------------------------
# Fused kernel for window process for SwinTransformer
# Copyright (c) 2022 Nvidia
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
import torch
import swin_window_process
class WindowProces... |
20337215e8529e06188d189092442472f125b07726f7295095481cce0361ba77 | Python | 2,016 | 57 | """Average runs with same phase encoding axis."""
import os
import numpy as np
import nibabel as nb
import glob
# =============================================================================
DATADIR = '/Users/sebastiandresbach/data/neurovascularCouplingVASO/Nifti'
# Set subs to work on
SUBS = ['sub-07']
DIRECTIONS =... |
1f0d736f030a20641d2baa33a520c4b53cc8cfac63733872641a9d58c24cf604 | Python | 2,018 | 50 | def test_multi_roi_timeseries():
import matplotlib.pyplot as plt
from os import path
from samri.plotting import summary, timeseries
from samri.utilities import bids_substitution_iterator
from samri.fetch.local import roi_from_atlaslabel
substitutions = bids_substitution_iterator(
sessions=[
'ofM',
'ofMaF... |
f038d559977661879254babf9f77e412419cad36d3b75effe1a057ad85c76e47 | Python | 2,019 | 55 | import os
import re
import json
import torch
project_root = '/ccb/cybertron/khchao/splam-analysis-results/'
output_dir = f'{project_root}train/results/MANE/REF_junctions/'
def main():
JUNC_COUNTER = 0
os.makedirs(output_dir, exist_ok=True)
fw = open(f'{output_dir}ref_d_a.bed', 'w')
with open(f'{pro... |
12f5ce6565d8e124eceb18263a3fd06cc015c09f4b8e412772ddb919ed7364fc | Python | 2,020 | 57 | from typing import Hashable, List, Mapping, Tuple, Union
import torch
from torch import Tensor
__all__ = ["tensor_op", "to_device_dtype"]
data_type = Union[Tensor, List[Tensor], Tuple[Tensor], Mapping[Hashable, Tensor]]
def tensor_op(data: data_type, fn: str, *args, **kwargs) -> data_type:
"""
Invokes a fu... |
1931a2bef1b837301cafd9aa59220478d6f9914fe6eb25e270369ab85e3b827b | Python | 2,021 | 54 | # Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under th... |
708c7515a085ca75532d4c9664bc783f2b51be4f2747f9d68d17cf256df76602 | Python | 2,022 | 54 | import numpy as np
import argparse
import pickle
import sys
if __name__ == '__main__':
parser = argparse.ArgumentParser('Parse the results of the GLM fit grid search')
parser.add_argument('grid_file', type=str, help='path to grid search file file')
parser.add_argument('-l21', '--fix_l21', type=float, de... |
9fac3b2df9afe6e723e0b6de859192942440a79783de5da5f1f7200ac04acfc7 | Python | 2,022 | 54 | import os
from ..utils import logger
try:
from huggingface_hub import snapshot_download
except:
huggingface_hub_installed = False
def snapshot_download(*args, **kwargs):
raise ImportError('huggingface_hub is not installed. If weights are not avaliable, please install it by running: pip install hug... |
1a009267d8f520003924fdac3355cdc844892dee24899313a7b4f14f6e592006 | Python | 2,023 | 66 | from __future__ import print_function
import torch.utils.data as data
import os
from PIL import Image
from utils import preprocess
class VOCSegmentation(data.Dataset):
CLASSES = [
'background', 'aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus',
'car', 'cat', 'chair', 'cow', 'diningtable', 'dog', ... |
1c28c6bac84af3471bcc0a73791ac3de4cda72bae59acff22902848d671d6876 | Python | 2,023 | 45 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
a752a34591ff718c2fa2adf631e26109171fd1c557d25a3f98de54a6d37b5e7a | Python | 2,023 | 57 | import copy
import torch
from mmengine.model import BaseDataPreprocessor
from lqit.registry import MODELS
from lqit.utils import ConfigType
@MODELS.register_module()
class BatchDataPreprocessor(BaseDataPreprocessor):
def __init__(self,
data_preprocessor: ConfigType,
multi_inpu... |
6097d979b15064c71660db56aace6512aba715edf5c9dc4552e55c8dafcd0691 | Python | 2,024 | 69 |
def load_training_data(dataFile, validation_split=0, axes=None, n_images=None, verbose=False):
f = np.load(dataFile)
X, Y = f['X'], f['Y']
if axes is None:
axes = f['axes']
axes = axes_check_and_normalize(axes)
assert X.shape == Y.shape
assert len(axes) == X.ndim
assert 'C' in ax... |
07a0d6d8fef59d29718ddab074c6a72cf3cb455bc7a35812c085dfe5c69073b5 | Python | 2,025 | 71 | # Copyright 2026 Google LLC.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
3ac60c452e03192d90a2e24784f36591722b94a9c025bb4b66591482b173a027 | Python | 2,025 | 59 | import io
import tarfile
import time
import uuid
from typing import Any, Callable, Dict, List, Optional, Union
import pyarrow
from ray.data._internal.datasource.webdataset_datasource import (
_apply_list,
_default_encoder,
_make_iterable,
)
from ray.data.block import BlockAccessor
from ray.data.datasource... |
c29122f45974b63c2ba96a3b03bca313f8e5167740b01dc7cbb795cd5805484a | Python | 2,025 | 46 | import timeit
import argparse
from pyrosetta import *
parser = argparse.ArgumentParser(description="Specific FastRelax procedure for GDFold2 predictions")
parser.add_argument('--input', type=str, help='Input unrelaxed model')
parser.add_argument('--output', type=str, help='Output model name (.pdb format)')
pars... |
29a352e2b431a05304e6baf6e7805027110145e815f73061fd390b129ddef347 | Python | 2,027 | 55 | import numpy as np
import pytest
import torch
from flyvis.datasets import rendering
@pytest.fixture(scope="module")
def boxeye() -> rendering.BoxEye:
return rendering.BoxEye(15, 13)
def test_init(boxeye: rendering.BoxEye):
assert boxeye.extent == 15
assert boxeye.kernel_size == 13
assert boxeye.rec... |
ed244e9b7a177a9123d4331fd5f997c2f3282bdc337faa24d2392b88413b2a92 | Python | 2,027 | 61 | from __future__ import annotations
from abc import abstractmethod
from .. import settings
class BaseAlgorithm:
def __init__(
self,
batch_key: str | None = "_batch_annotation",
labels_key: str | None = "_labels_annotation",
seen_result_key: str | None = None,
result_key: s... |
29e2b6ae7e3f83508f9bd04654380ea84232580227b880edea0827bf68312bef | Python | 2,029 | 64 | #!/usr/bin/env python
from __future__ import print_function
import argparse
import glob
import gzip
import math
import numpy as np
import os
import random
def parse_args():
parser = argparse.ArgumentParser("Makes plots and reports details of vcfeval output")
parser.add_argument('--input_qual_file', '-i', dest... |
b9e53e7758b4782926a40d1bd89a798e71b21aaae23d6d0351c14998ea2009e0 | Python | 2,029 | 59 | import os
import shutil
import argparse
import numpy as np
from sklearn.model_selection import StratifiedKFold
"""Generate K splits train-val for K-fold cross validation"""
def load_train_data(path, dtype_data=np.uint8, dtype_label=np.uint8):
X = np.fromfile(path + "/X_train.bin", dtype=dtype_data)
y = np.fr... |
2120f81aa59f5de4f92f25509a9d93f06c8c7924de396efc11609bcf0d0db3d7 | Python | 2,031 | 55 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
6cd94b4ee8798f8478dc21e600d288ee1e989354b4867e37974b942b06cc2d27 | Python | 2,031 | 72 | # __neuron_serve_code_start__
from io import BytesIO
from fastapi import FastAPI
from fastapi.responses import Response
from ray import serve
app = FastAPI()
neuron_cores = 2
@serve.deployment(num_replicas=1)
@serve.ingress(app)
class APIIngress:
def __init__(self, diffusion_model_handle) -> None:
self... |
4936ae59f77eaaba3e1c22f04f666b2d03b26e6e79698807c1a275feb1ff6017 | Python | 2,033 | 64 | # Copyright 2023 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
e6b0207bd6ac0c0ea7798b7844b9fcb4a9edaf216229ff6ce36938e1b41cbed5 | Python | 2,033 | 54 | """Minimal HTTP listener for BackgroundUploadTest (not part of the product).
usage: python3 background_listener.py PORTFILE OUTPREFIX [DELAY_SECONDS]
Binds 127.0.0.1 on a free port, writes the port number to PORTFILE, serves one POST,
writes the raw body to OUTPREFIX.body and then the request headers (one "name: valu... |
83d79cc90909480715f74336af2ec06b05028aa0557801c0708c7be776b76fbb | Python | 2,036 | 81 | # flake8: noqa
"""
This file holds code for the runtime envs documentation.
FIXME: We switched our code formatter from YAPF to Black. Check if we can enable code
formatting on this module and update the paragraph below. See issue #21318.
It ignores yapf because yapf doesn't allow comments right after code blocks,
but... |
7dce6468a72192ea9bbeaf3502a0d8618ae87981f0707f83b5f316e6ee8c15c2 | Python | 2,037 | 67 | import numpy as np
def split_tx(X_tf, segment_lengths):
'''
Split up a seemingly continuous X_tf into a list of its contiguous segments
'''
n_t = X_tf.shape[0]
segment_idx = np.cumsum(segment_lengths)
assert segment_idx[-1] == n_t
segment_idx = segment_idx[:-1]
return np.split(X_tf, seg... |
a9f2b517c532f1d5c9dfb9a11f5570a0427310bbd47f7e8166cd7ec832d3db1b | Python | 2,037 | 72 | import numpy as np
import pytest
import torch
import torch.nn as nn
from sinabs.layers import LIF, StatefulLayer
def test_stateful_layer():
layer = StatefulLayer(state_names=["v_mem"])
assert not layer.is_state_initialised()
assert layer.v_mem.shape == torch.zeros((0)).shape
layer.reset_states()
... |
ef74c58a778abe16ad79a91b08c7959dd822925bffc2f3c470e9478636aaaf71 | Python | 2,039 | 69 | import cv2 # noqa: F401 — preload libtiff before HIPT/torchvision shadows it (omicverse vendored patch)
import argparse
import numpy as np
from einops import reduce
from utils import load_image, save_image, load_mask
from image import crop_image
def adjust_margins(img, pad, pad_value=None):
extent = np.stack([... |
7ea3e2c9deb6e5f9f18d4474d43a64d401b749d384c70a99fc4ac7ec3f82f644 | Python | 2,040 | 60 | # Copyright (c) DP Technology.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import absolute_import, division, print_function
import yaml
import os
from addict import Dict
from .base_logger import logger
class YamlHandler... |
415eae14cb1b4a61c5c763a3b86385fcd1b913774c5d0906b5772b03165096e0 | Python | 2,041 | 72 | from ray._common.utils import env_bool
try:
from ray._raylet import (
AuthenticationMode,
get_authentication_mode,
is_k8s_token_auth_enabled as _is_k8s_token_auth_enabled,
validate_authentication_token,
)
_RAYLET_AVAILABLE = True
except ImportError:
# ray._raylet not av... |
86b582cbfae33945478f83bfd8a5b2f7393b5b14b857b5d83abf9cad635ffab7 | Python | 2,041 | 50 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
287fff0aff5398432b2b0ddee3341f2f587e063b64e2fc4a05749ebf2255d255 | Python | 2,042 | 64 | # Copyright 2023 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
506e869a8ee71b3626c842aa5b59d2e67e95e8287bad0c26b6ea86e949b5beee | Python | 2,043 | 53 | # Ultralytics YOLO 🚀, GPL-3.0 license
from ultralytics.yolo.utils import LOGGER, TESTS_RUNNING
from ultralytics.yolo.utils.torch_utils import get_flops, get_num_params
try:
import comet_ml
assert not TESTS_RUNNING # do not log pytest
assert comet_ml.__version__ # verify package is not directory
except ... |
8f36529804e447bed1e40b24cb6ff9730d29029a9908cadc7900bcf21d9d1330 | Python | 2,043 | 53 |
from functools import partial
from abberior import microscope
EXC_ID = 5
STED_ID = 6
def set_powers(conf, power, laser_id):
"""
Sets the power of a laser across all channels
:param conf: A configuration object
:param power: Power of the laser in [0, 100]
:param laser_id: ID of the laser in Imsp... |
1dc3ca0a4198eb14f8ec2106e1f4418b8b26f88803d68e1903d00f6742ff78dc | Python | 2,046 | 75 | # -*- coding: utf-8 -*-
from ._version import __version__, __version_info__
from ._history import figure_history
from .figures import (
Figure as figure,
gcf,
scf,
auto_figure,
show,
view,
reset_camera,
save_fig,
screenshot_fig,
close,
zoom_to_contents,
)
from .plots.Arrow ... |
80eff3e64ab31996f41b99146ef16b4998b2ef552c627d54ac4181dea7f545a8 | Python | 2,047 | 56 | import torch
from ..distances import CosineSimilarity
from ..losses import GenericPairLoss
from ..utils import loss_and_miner_utils as lmu
class IntraPairVarianceLoss(GenericPairLoss):
def __init__(self, pos_eps=0.01, neg_eps=0.01, **kwargs):
super().__init__(mat_based_loss=False, **kwargs)
self.... |
2862b29e0f42a250589fbb6a5c0370a8aed65733381eeda459969a3c37b47ef4 | Python | 2,048 | 60 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""aihwkit example 9: simple network with one layer using
deterministic pulse trains for update.
Simple network that consist of one analog layer. The network ai... |
c0b5d9eb40470ec3b24d038a86b73a5141e7dbd0f0b08022475c139063a56fad | Python | 2,049 | 38 | """
The code for the research presented in the paper titled "Enabling inverse design of plasmon-based nonlinear square resonators with deep neural networks."
This code corresponds to the article's inverse Deep Neural Network (DNN) section.
This code regenerates the Fig. 7b and c of the paper.
Please cite the pape... |
df6c6ef315fc7327508cec8c76abe3ce0d568291e6e23150bbbf6bdb65a631e7 | Python | 2,049 | 62 | # -*- coding: utf-8 -*-
"""
Created on Fri Apr 30 10:34:00 2021
@author: ju-bar
Functions and classes handling atom type data
This code is part of the 'emilys' repository
https://github.com/ju-bar/emilys
published under the GNU General Publishing License, version 3
"""
atom_type_symbol = ['Void' ,
'H' , 'He' ... |
edecb056749489ecee7fa42d7987579ff61e53c0d52c5405218e871d6c838013 | Python | 2,049 | 70 | # __sync_actor_start__
import ray
@ray.remote
class TaskStore:
def get_next_task(self):
return "task"
@ray.remote
class TaskExecutor:
def __init__(self, task_store):
self.task_store = task_store
self.num_executed_tasks = 0
def run(self):
while True:
task = ra... |
3c6b317465545aa13758772db44ddeb10ebb3bb8af80115548cca127282d4aaf | Python | 2,050 | 91 | # flake8: noqa
# __cancel_start__
import ray
import asyncio
import time
@ray.remote
class Actor:
async def f(self):
try:
await asyncio.sleep(5)
except asyncio.CancelledError:
print("Actor task canceled.")
actor = Actor.remote()
ref = actor.f.remote()
# Wait until task i... |
36791ebc198676031acafd4eca3e565f2a742da182f30253eedefe707a901960 | Python | 2,051 | 69 | import numpy as np
from scipy import signal
def global_inh_model(r0, r_bar, T, dt, W, tau, DMatrix):
# Simulates the rate equations
# Function inputs
# r0: rates to start at
# r_bar: desired steady state solution
# T: sim end
# dt: size of timestep
# W: connectivity matrix
#... |
89fb6730766d02c3d9df01c33cf091dd58132a30ac8cd9590084307b35b0ca7b | Python | 2,051 | 53 | import statistics
from typing import Iterable
import numpy as np
def rescale_method_1(scaling_factors: Iterable[int], lambda_: float = 0.5) -> float:
"""
This method will use the average (scaled by `lambda_`) of the computed re-scaling factor
for the pooling layer(s) feeding into a convolutional laye... |
a99b88baaf25c1fad9eb7e1eef03e1e5568c9781c5899e00a51fd9e2d1c23c73 | Python | 2,051 | 47 | import sys, os
os.environ.setdefault('PROJECT_DIR', '.')
sys.path.append(os.environ['PROJECT_DIR'])
import argparse
import concurrent.futures as cf
import pandas as pd
from src.data.buckets import MakeBuckets
from src.features.tokenizer import Tokenizer
def main():
parser = argparse.ArgumentParser()
... |
f82671b04ba987b48d510500b774ec0445d054d341e41eb6edd29bf04bb1c665 | Python | 2,051 | 45 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
1abc71baea54445a55f9ac59b3a623142ea5ebe7f813eed95bb67aa4e8b5c902 | Python | 2,052 | 66 | from typing import List
from ipywidgets import widgets
from data_profiling.report.presentation.core.frequency_table_small import (
FrequencyTableSmall,
)
class WidgetFrequencyTableSmall(FrequencyTableSmall):
def render(self) -> widgets.VBox:
return frequency_table_nb(self.content["rows"])
def freq... |
6fad53f1b43405ee72e27616585036df94b4ecccf9ab239d84c08c59e9c38b06 | Python | 2,052 | 66 | import enum
import logging
import os
from typing import TYPE_CHECKING
from .autoscaling_actor_pool import ActorPoolScalingRequest, AutoscalingActorPool
from .backlog_aware_actor_autoscaler import BacklogAwareActorAutoscaler
from .base_actor_autoscaler import ActorAutoscaler
from .default_actor_autoscaler import Defaul... |
110e681cc7235cf66428ad26810151af1cce8be023b80bb2f1d85ab85dcc7100 | Python | 2,054 | 67 | """
3 comparisons (6 panels)
Active vs. passive %sv, loading sim, and dimensionality
for A1 / PEG
"""
import os
rdir = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))
import sys
sys.path.append(rdir)
from settings import RESULTS_DIR
import scipy.stats as ss
import pandas as pd
import numpy as np
i... |
2e33790e9cdc7f1117aba012e6560132b683d77b99cfdd7c4ae4608e30b807a2 | Python | 2,054 | 59 | import torch
class LagrangianOptimization:
min_alpha = None
max_alpha = None
device = None
original_optimizer = None
batch_size_multiplier = None
update_counter = 0
def __init__(self, original_optimizer, device, init_alpha=0.55, min_alpha=-2, max_alpha=30, alpha_optimizer_lr=1e-2, batch_... |
861f090466a7811179b27786355fbe53e31e684bbfba0e354564b4a1b43dd826 | Python | 2,054 | 65 | import numpy as np
DATA_ROOT = '../data/output/'
PROBLEMATIC_TRAIN_VIDEOS = ['4.4.1']
class TrainValidSplit:
def __init__(self, feature_tag='sep_09'):
self.feature_tag = feature_tag
self.train_fpath = f'{DATA_ROOT}train_{self.feature_tag}.txt'
self.valid_fpath = f'{DATA_ROOT}valid_{self.fe... |
8d87a8715f1fe5be8ed0097dc1251b4fa18ce4f8d84e561daa57caf327cec17e | Python | 2,054 | 44 | import os
import glob
import nibabel as nib
import numpy as np
from utils_mirror import find_corners, mesh_sides
def mesh(initial_path, initial_save_path, margin, res):
rotated_path = sorted(glob.glob(os.path.join(initial_path, '*')))
for idx, path in enumerate(rotated_path):
path_right = sorted(glob.g... |
a8af571ec2cee41f20b79db91d38288a37d65c76d32d0212217afd02dc72cae9 | Python | 2,054 | 60 | import argparse
import h5py
import os
from glob import glob
import nilearn.input_data
from tqdm import tqdm
LOAD_CONFOUNDS_PARAMS = {
"strategy": ["motion", "high_pass", "wm_csf", "global_signal"],
"motion": "basic",
"wm_csf": "basic",
"global_signal": "basic",
"demean": True,
}
def main(args):
... |
084de507948fce6818730fb20306ae7558ae32ee36e694813571e4f195e0a98c | Python | 2,055 | 68 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
import random
import numpy as np
import pytest
from fairchem.data.oc.core import Adsorbate, AdsorbateS... |
d66704ba2a911b2ffa5f172c7be265fdc0e33fa482e776a44ab7af705a751b62 | Python | 2,055 | 69 | # -*- coding: utf-8 -*-
"""
Created on Sun Jul 1 12:30:00 2019
@author: ju-bar
Monte-Carlo tools
This code is part of the 'emilys' repository
https://github.com/ju-bar/emilys
published under the GNU General Publishing License, version 3
"""
# %%
from numba import jit # include compilation support
import numpy as np ... |
7004b423416666a9072b5a327de7785c02a81ac4df40b6dbe69d34165172faea | Python | 2,056 | 61 | # -*- coding: utf-8 -*-
"""This dummy vtk module mimics the default vtk module structure
whilst only loading the libraries and corresponding dlls that
vtkplotlib uses. This makes import quicker and PyInstaller builds
smaller.
"""
from vtkmodules.vtkCommonCore import (
VTK_ID_TYPE, vtkCommand, VTK_COLOR_MOD... |
c312411eac1a317b7a76e50b7a41c9102368f0d7fb47023e0fd8b5ecb4656bb1 | Python | 2,057 | 53 | import numpy as np
import torch
from ..distances import CosineSimilarity
from ..utils import common_functions as c_f
from ..utils import loss_and_miner_utils as lmu
from ..losses.generic_pair_loss import GenericPairLoss
class TupletMarginLoss(GenericPairLoss):
def __init__(self, margin=5.73, scale=64, **kwargs):... |
8290c21eab3850c87f0dce2a647767d045642201405a70551815aae39e194848 | Python | 2,058 | 59 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
from typing import TypeVar
import pandas as pd
from fairchem.core.components.benchmark import JsonDFR... |
a8b2096137644c7f81751089b05f3f62d1fe79132aba4e782e9970066017b1b0 | Python | 2,059 | 76 | import os
import pathlib
import tempfile
import h5py
from deepinterpolation.inference_collection import core_inference
from deepinterpolation.generator_collection import EphysGenerator
def _get_generator_params():
train_path = os.path.join(
pathlib.Path(__file__).parent.absolute(),
"..",
"... |
c4d2fb3d83349e388b3a73e96b263a469ca9f3fd72a3221f915d96a94aa54da3 | Python | 2,059 | 62 | from typing import Callable, Optional
class TrackedActor:
"""Actor tracked by an actor manager.
This object is used to reference a Ray actor on an actor manager
Existence of this object does not mean that the Ray actor has already been started.
Actor state can be inquired from the actor manager trac... |
7c6c2e4130ee4a775d1af4c749c786127c4b132745e9d6c00ca569634d3c7440 | Python | 2,060 | 48 | # -----------------------------------------------------------------------------
# I/O
# learning data directory, train.bin and valid .bin are expected. You should prepare them using tokenize.py
data_dir = 'directory_containing_train.bin/val.bin'
out_dir = 'output_directory' # output directory
log_dir = os.path.join(o... |
5e7825f25a7ed7c725f78e5ebf35b0363e6b2fa5a00e0d99e6f9dd39d9fa37d5 | Python | 2,062 | 70 | # codign_genes.py
# mmsplice_splicemap.py
# absplice_dna.py
import snakemake
import click
@click.group()
def cli():
pass
@cli.command()
@click.argument("input", type=click.Path(exists=True))
@click.argument("output", type=click.Path(exists=False))
def codign_genes(input, output):
import pyranges as pr
... |
7665c58e7f585fc7f42b9e7667931308ccd521f2dc28e9ff747e37ecb38b6623 | Python | 2,062 | 57 | #!/usr/bin/env python
# coding: utf-8
import torch
import torch.nn as nn
from Actor1 import init_weights
class Critic(nn.Module):
def __init__(self, OBS_DIM, ACTION_DIM, TARGET_DIM, RNN_SIZE, FC_SIZE, RNN):
super().__init__()
self.OBS_DIM = OBS_DIM
self.ACTION_DIM = ACTION_DIM
... |
f1d5669ea03e6f4113dca9690f72c63c62ec5ce3f33066b94393bb4b19168948 | Python | 2,064 | 72 | # -*- coding: utf-8 -*-
from torch.utils.data import Dataset
from Bio.PDB import Polypeptide
import numpy as np
import torch
import pandas as pd
class PepCA_dataset(Dataset):
def __init__(self, mode,data_set,df_dir = './data/'):
aa = 'ACDEFGHIKLMNPQRSTVWY'
aa2tensor_dict = {}
fo... |
d30622ac7ab3dd4eee9c8450833ac0eac82670d1cdd4306f8ea1599149cbd727 | Python | 2,065 | 57 | import tfbio
from tfbio.data import Featurizer
import pybel
import os
import numpy as np
import argparse
max_dist = 35
resolution = 2
scale = 0.5
if __name__=='__main__':
parser = argparse.ArgumentParser(description='Data Generator Parameters')
parser.add_argument('--database', type=str)
... |
caf5b2571ac04265b29f81a716ac04d2eba9b7c4aec4af54f04c56583725384a | Python | 2,066 | 65 | """Computes and saves adjacency/distance/coulomb matrices for a dataset."""
import time
from tap import Tap
from GR_pKa.atomic_matrices import mol2matrix
from GR_pKa.features import save_features
from GR_pKa.data import get_smiles
from GR_pKa.utils import makedirs
class Args(Tap):
data_path: str # Path to data... |
dc14b54ab9d0a81b54ee7ab24fc15b6ccc52d135565441d4504efa25280bdf64 | Python | 2,066 | 60 | _base_ = 'ssd300_120e_urpc-coco.py'
# model settings
input_size = 512
model = dict(
neck=dict(
out_channels=(512, 1024, 512, 256, 256, 256, 256),
level_strides=(2, 2, 2, 2, 1),
level_paddings=(1, 1, 1, 1, 1),
last_kernel_size=4),
bbox_head=dict(
in_channels=(512, 1024, 5... |
cf7fece94c44439616ce136ceb8c5342daf0ec38579c811927d2006fd8808009 | Python | 2,068 | 39 | import logging
from datetime import datetime
from agent.data.entities.config import DEV_ITEM_FILTER, TEST_ITEM_FILTER, DEV_LABEL, TEST_LABEL
from agent.data.entities.config import SKIP_VAL_ITEM_FILTER, SKIP_VAL_LABEL
from agent.classifiers.fd_naive_item_classifier import fd_naive_classifier, evaluate_items_for_filter... |
2f2c40385ca01056013a9047a65e17519c6a187dd7cda3e9b307cd77a664dfc0 | Python | 2,069 | 69 | import matplotlib.pyplot as plt
import seaborn as sns
ucd_install=False
class BulkDeconvolve(object):
r"""
Bulk RNA-seq deconvolution using UCDeconvolve.
This class provides an interface to the UCDeconvolve platform for deconvolving
bulk RNA-seq samples into cell-type proportions using curated ... |
835686fee9850b0ddd1aa97cf68ed5ba196ef3f79bab2eb47fa31440465424de | Python | 2,069 | 60 | import atexit
import os
import signal
import sys
import time
"""
This is a lightweight "reaper" process used to ensure that ray processes are
cleaned up properly when the main ray process dies unexpectedly (e.g.,
segfaults or gets SIGKILLed). Note that processes may not be cleaned up
properly if this process is SIGTER... |
a02e68cdbcdc42a9a660b0c7df32f84eb413276e36e6480af8c2704d4276e1ae | Python | 2,070 | 72 | import argparse
import os
import time
import numpy as np
import pandas as pd
from tqdm import tqdm
from collections import defaultdict
marks = ['H3K4me1', 'H3K4me3', 'H3K9me3', 'H3K27me3', 'H3K36me3', 'H3K27ac', 'H3K9ac']
chromosomes = [f'chr{i}' for i in range(1, 23)] + ['chrX', 'chrY']
def parse_arguments():
p... |
13b906f55053a61ba9c69971a9eb94a972b7b1e40899371b1cae95ed2fcadf22 | Python | 2,071 | 39 | from data_processing.data_utils import *
from data_processing.embed import *
import os
# This script will process the raw data and embed using ESM-2.
"""First, process the raw x-species data"""
def make_xspecies_interactions(dataset, dir, target_dir, fasta_dir):
species_name = dataset.split('_')[0]
input_... |
383f029d80d392dd9e832c1d916f67fe1fdf83e318571251f1876c5773ff2012 | Python | 2,072 | 75 | """Utility functions for operations on pandas DataFrames."""
from typing import Iterable
from pandas import DataFrame
def filter_by_column_values(
dataframe: DataFrame, column: str, values: Iterable
) -> DataFrame:
"""
Return subset of dataframe based on list of values to appear in a column.
Args:
... |
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